Multiplexed Multimodal Single-Cell and Spatial Sequencing

Increasing dimensions and throughputs of single-cell genomics by multiplexing and combinatorial indexing design.
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Current single-cell sequencing studies are usually limited by the investment of precious samples and high experimental costs. We have developed an experimental workflow (mux-seq) and the company algorithm (demuxlet) which enables multiplexed single-cell sequencing of genetically different samples and demultiplexing based on natural genetic variations. This approach allows for increased cell input and reduced reagent costs, most importantly, it minimizes technical variations in the experiments. The multiplexed single-cell sequencing is now routinely performed in the lab and has been applied to study immune cells in autoimmune disease, cancers and infectious diseases including COVID-19.

To maximize the data generating potential, we have developed workflows that enable ultra-high throughput single-cell multimodal profiling (SCITO-seq) and spatial sequencing with single-cell resolution (XYZeq). By utilizing splint oligos, we have enabled combinatorial indexed dsc-seq of DNA-barcoded antibodies from greater than 105 cells per reaction using commercially available microfluidics, achieving a 20-times higher throughput of current single-cell sequencing capacity. We also further demonstrated modified splint oligo designs that extend SCITO-seq to achieve compatibility with commercially available DNA-barcoded antibodies of greater than 150 markers and simultaneous profiling of whole transcriptome and surface protein expression from the same cell. To simultaneously map transcriptome and spatial localization of single cells in tissue slices, we have developed an innovative workflow XYZeq. It uses combinatorial indexing in microwells to encode spatial metadata into scRNA-seq libraries. We have recently applied XYZeq to profile heterotopic mouse liver and spleen tumor models to capture transcriptomes from tens of thousands of cells across a total of eight tissue slices. 


Alumni Research Team

Rachel Gate, Co-founder of Dropprint Genomics 

Lenka Maliskova, Lab Manager at UCSF Genomics Colab

Meena Subramaniam, Co-founder of Dropprint Genomics

Sasha Targ, MD student at UCSF medical school

Selected Publications

Multiplexed Droplet Single-Cell RNA-Sequencing Using Natural Genetic Variation
Nature Biotechnology. 2017
SCITO-Seq: Single-Cell Combinatorial Indexed Cytometry Sequencing
bioRxiv. 2020
XYZeq: Spatially-resolved single-cell RNA-sequencing reveals expression heterogeneity in the tumor microenvironment
Science Advances. 2021

Research Team

George Hartoularos

Graduate Student, BMI, NSF Graduate Research Fellowship Recipient

Byungjin Hwang, Ph.D.

Postdoctoral Fellow

David Lee

Staff Research Associate

Elizabeth McCarthy

Graduate Student, MSTP, Bioinformatics, NIH F30 Award Recipient

Cody Mowery

Graduate Student, MSTP, BMS, NIH F30 Award Recipient

Anton Ogorodnikov, Ph.D.

Bioinformatics Scientist

Yang Sun, Ph.D.

Lab Manager


Media highlights of Ye Lab's research.
We Need Volunteers To Improve Our Understanding of the Human Immune System
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